Tyler Angell

Full Stack Web Developer

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I've been building web applications since 2019. I'm a self-taught full stack web developer with experience building applications in Next.JS and the PERN stack.

When I'm not at my computer, you may find me at the gym, outside with my two wonderful dogs, or online playing video games.

If you think I would make a good fit on your team or would like to leave some feedback, contact me at my email below. I look forward to hearing from you!

View Resume


Thunderbolt Images

This e-commerce site was designed in Figma and built using Next.js. The site uses Redux Toolkit for the shopping cart, Paypal Standard Checkout for payment processing, and PosgreSQL on the backend. The live link is to a production deployment to preserve the integrity of the client's analytics.

Next.js, Redux Toolkit, Paypal, Prisma, PostgreSQL, Google Analytics, Figma

See live

Face Detection App

This full stack web app uses Clarifai's Face Detection model and API to detect faces in user submitted image URLs. The backend handles the requests for signing in, registration, and interfacing with Clarifai's API. The database was built using PostgreSQL and stores username, password (encrypted), and entry count for image submissions. The app was deployed to Heroku and is in the process of being deployed to another platform.

React, Redux, Node, Express, PostgreSQL

Source code

Robofriends with Redux

This app takes a user-typed input and filters a list of users/robots received from the JSONPlaceholder API. Pictures of robots are generated using Robohash based on the unique id of the received user list. There are 2 actions: a synchronous action for handling user input and an asynchronous action (thunk) for handling the API call. This app is deployed on Netlify.

React, Redux, REST API

See liveSource code

Millimeter Wave and THz Project

This research project investigated the effects of probe placement error on calibration accuracy. Python was used to introduce Gaussian noise for simulating error, to code the TRL algorithm, and plot results. This research provides evidence to support that percent error increases exponentially as a function of probe displacement.


See project


This project uses Python to compare the forecasting abilities of Long Short-Term Memory (LSTM) networks and Facebook's Prophet. This study discusses these algorithms, how to control them, and briefly compares them head-to-head.

Python, ML, LSTM, Prophet

See project


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